Name
Title | ||
|---|---|---|
LTO: Lazy Trajectory Optimization with Graph-Search Planning for High DOF Robots in Cluttered Environments |
Abstract | ||
|---|---|---|
Although Trajectory Optimization (TO) is one of the most powerful motion planning tools, it suffers from expensive computational complexity as a time horizon increases in cluttered environments. It can also fail to converge to a globally optimal solution. In this paper, we present Lazy Trajectory Optimization (LTO) that unifies local short-horizon TO and global Graph-Search Planning (GSP) to generate a long-horizon global optimal trajectory. LTO solves TO with the same constraints as the original long-horizon TO with improved time complexity. We also propose a TO-aware cost function that can balance both solution cost and planning time. Since LTO solves many nearly identical TO in a roadmap, it can provide an informed warm-start for TO to accelerate the planning process. We also present proofs of the computational complexity and optimality of LTO. Finally, we demonstrate LTO's performance on motion planning problems for a 2 DOF free-flying robot and a 21 DOF legged robot, showing that LTO outperforms existing algorithms in terms of its runtime and reliability. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICRA48506.2021.9561502 | 2021 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA 2021) |
DocType | Volume | Issue |
Conference | 2021 | 1 |
ISSN | Citations | PageRank |
1050-4729 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuki Shirai | 1 | 2 | 1.77 |
| Xuan Lin | 2 | 0 | 2.37 |
| Ankur Mehta | 3 | 0 | 2.03 |
| Dennis W. Hong | 4 | 5 | 4.99 |